On the front page of a recent edition of the Wall Street Journals’ Business and Finance section was an article titled, “Overtime Pay Becomes Costly”. The article reports on data suggesting that overtime costs are increasing at significant rates.

The argument made is that the US economy is approaching full employment and so overtime costs are rapidly increasing. The result will lead to increased costs, and at some point increased inflation. This all signals, so the theory goes, to a growing economy and one approaching the old normal.

But if we look at the underlying story in the article, and throw in additional data, we can see that this story impacts productivity, production, and when and how firms decide to increase investment in capital equipment, including information and technology.

First, the core data. There are several examples of enterprises that claim that job openings are not being filled and to meet production targets, overtime is being increased. The lack of job seekers is to be compared to another data point such as labor force participation rate.

The labor force participation rate has been very low for some time, and this reflects another complication in looking at full employment. The labor force participation reflects things like population aging whereby folks get old and decide to no longer search for work. It also reflects the decline in the working-age population that give up looking.

These folks give up looking for a number of reasons. One perspective is that government hand-outs are high enough to disuade some from looking to work for about the same amount of money. Some feel that there is no hope of getting work again so just give up. Interestingly the labor force participation rate has been ticking up slightly in recent periods so the argument that we are close to full employment maybe less valid – at least until the participation rate approaches a more natural rate.

But what is the natural rate? The recession and long, slow recovery, often referred to as the new normal, has upended all manner of natural rates. Inflation is being rethought – the Fed’s public expectation and goal of 2% seems to be less a natural rate these days since we fail to get and keep at 2%. Interest rates have been at low levels or near-zero for extensive periods and are only now increasing.

The rate of “full employment” itself may have changed – economists just don’t know. Full employment describes the level of unemployment that cannot be lowered without adding increased wages, thus driving up inflation. Since overtime is increasing, it means costs are increasing.

The article also calls out the challenge for business leadership. As overtime costs increase, there is only so much you can incur. First it becomes prohibitive and margins may fall. Second workers themselves may max-out and stop responding to calls for more overtime due to the opportunity costs of leisure time.

So the decision faced by all leaders is this: When to substitute additional overtime pay for increased investment in productivity-inducing capital and this includes information and technology?

The article notes that it can take many months for investments in new equipment and software to yield an increase in productivity. Such an increase would lead to more outcome but at the same or lower costs – therefore without increasing overtime.

Did your business invest in new productivity-inducing equipment or software in the last year? Did it yield the increase in output as expected? If so, your overtime costs won’t be going up as fast as your competitors.

Do you invest now, assuming demand will hold up given the nature of this strange recovery? If you assume demand will hold up, and that full employment is near, then yes you need to invest now.

But each industry will exhibit different situations of demand, employment, and productivity-including capabilities. It leads to a real interesting time. This is why business leaders are paid the big bucks – they are charged with making this decisions – and betting with incomplete information. Such is life.

(This post originally appeared on Andrew White's Gartner blog, which can be viewed here).

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